Analysis on the Change of Arable Land Area and its Driving Force in Hefei City

2013 ◽  
Vol 726-731 ◽  
pp. 4879-4882
Author(s):  
Hong Mei Zhang ◽  
Yang Gao
Keyword(s):  
Principal Component Analysis ◽  
Driving Forces ◽  
Arable Land ◽  
Principal Component ◽  
Component Analysis ◽  
Land Resource ◽  
Cultivated Land ◽  
Land Change ◽  
Land Area ◽  
Per Capita

In recent years, the decrease of total arable land area and the area per capita of available arable land resource are serious problems in China. These problems will become more serious with the development of economy. In this paper, based on the statistical data of cultivated land in Hefei city from 1998 to 2009, their driving forces of the cultivated land change were analyzed by means of principal component analysis. The results showed the changing trends. The total and per capita of cultivated land were declining, but the speed of change was not the same. The sharp decrease was occurred in the period of 2002-2005. Nine affecting factors having influenced on cultivated land change which were analyzed by principal component analysis. The results show that population growth, economic development and efficiency of agricultural production were main driving forces affecting cultivated land change in Hefei city.

The Analysis of Dynamic Change of Cultivated Land and Driving Forces in Suzhou City

2012 ◽  
Vol 616-618 ◽  
pp. 1421-1424
Author(s):  
Hai Min Su ◽  
Ai Xia He
Keyword(s):  
Principal Component Analysis ◽  
Survey Data ◽  
Social System ◽  
Driving Forces ◽  
Dynamic Change ◽  
Arable Land ◽  
Principal Component ◽  
Cultivated Land ◽  
Suzhou City ◽  
Per Capita

According to statistical and survey data from 1991 to 2010 at provincial and county levels, trend of cultivated land change and its driving forces in Suzhou City during the last 20 years were discussed in this article. It was found that: since 1990s, the total area of arable land and per capita availability were reducing; as a result of the principal component analysis, the 10 driving forces of arable land were analyzed which could be classified into three types, i.e, the development of economy, social system and population and progress of science and technology in agriculture. As to the economy factors, population and social system factors were the main driving forces, which play an important role in the change of cultivated land.

Analysis and Forecast of the Arable Land Resource and Food Production Safety in Anhui Province

2012 ◽  
Vol 253-255 ◽  
pp. 229-232
Author(s):  
Hai Min Su ◽  
Ai Xia He
Keyword(s):  
Food Production ◽  
Arable Land ◽  
Anhui Province ◽  
Land Resource ◽  
Cultivated Land ◽  
Land Area ◽  
Dynamic Changes ◽  
Pressure Index ◽  
Production Safety ◽  
Per Capita

The total dynamic changes of the cultivated land and food production from 1990 to 2010 in Anhui Province were analyzed using the statistic data and minimum cultivated land per capita and pressure index on cultivated land were calculated based on cultivated land, food production and population. At the same time, adopting GM(1,1) model, per capita cultivated land area, minimum cultivated land per capita and pressure index on cultivated land were forecasted in the future7 years. The results show that: (1) the total amount of the cultivated land decreased on the whole, steady decline early, while increased considerably late; Grain output went up steadily in the fluctuation in general; and the change of minimum cultivated land per capita and pressure index on cultivated land was not significant. (2) GM (1,1) gray model shows per capita cultivated land area, minimum cultivated land per capita and pressure index on cultivated land decreased, and arable land per capita is higher than the minimum per capita arable land area which descript farmland productivity levels higher than the level of food consumption.

scholarly journals Evaluation Methods of Water Environment Safety and Their Application to the Three Northeast Provinces of China

2019 ◽  
Vol 11 (18) ◽  
pp. 5135 ◽  
Author(s):  
Li ◽  
Sun ◽  
Yuan ◽  
Liu
Keyword(s):  
Principal Component Analysis ◽  
Water Resources ◽  
Chemical Oxygen Demand ◽  
Water Environment ◽  
Oxygen Demand ◽  
Principal Component ◽  
Component Analysis ◽  
Analysis Method ◽  
Industry Output ◽  
Per Capita

Focusing on the topic of water environment safety of China, this paper has selected the three northeast provinces of China as the research object due to their representativeness in economic development and resource security. By using the Entropy Weight Method, the Grey Correlation Analysis Method, and the Principal Component Analysis Method, this paper has first constructed a water environment safety evaluation system with 17 indicators from the economic, environmental, and ecological aspects. Furthermore, this paper has screened the initially selected indicators by the Principal Component Analysis Method and finally determined 11 indicators as the evaluation indicators. After indicator screening, this paper has adopted the improved Fuzzy Comprehensive Evaluation Method to evaluate the water environment safety of the three northeast provinces of China and obtained the change in water environment safety of different provinces from 2009 to 2017. The results show that the overall water environment safety of the region had improved first but worsened afterward, and that in terms of water safety level, Jilin Province ranked first, followed by Heilongjiang Province and Liaoning Province. The three factors that have the greatest impact on the water environment safety of the three provinces are: Liaoning—Chemical Oxygen Demand (score: 17.10), Per Capita Disposable Income (score: 13.50), and Secondary Industry Output (score: 11.50); Heilongjiang—Chemical Oxygen Demand (score: 18.64), Per Capita Water Resources (score: 12.75), and Concentration of Inhalable Particles (score: 10.89); Jilin—Per Capita Water Resources (score: 15.75), Chemical Oxygen Demand (score: 14.87), and Service Industry Output (score: 11.55). Based on analysis of the evaluation results, this paper has proposed corresponding policy recommendations to improve the water environment safety and promote sustainable development in the northeast provinces of China.

The Study on Dynamic Change of Cultivated Land Resources and Driving Forces - A Study Case of Lixian County, Hebei Province

2014 ◽  
Vol 707 ◽  
pp. 232-236
Author(s):  
Can Zhang ◽  
Hui Chun Shi ◽  
Xia Xia Lv
Keyword(s):  
Driving Forces ◽  
Dynamic Change ◽  
Arable Land ◽  
Reduction Rate ◽  
Principal Component ◽  
Economic Factor ◽  
Cultivated Land ◽  
Land Resources ◽  
Annual Reduction ◽  
Statistical Yearbook

In this paper, Lixian County 2001-2010 dynamic changes of cultivated land resources were studied. Studies have shown that: the past 10 years the average annual reduction rate of 0.72% Lixian County arable land, and the reduction since 2002, much faster, In the spatial region, most dramatic change is more economically developed society Liwu Town, Dabaichi Town, Xinxing Town and Liushi Town. According to the statistical Yearbook 2001-2010 review, we select factor and use principal component analysis. The main driving factors of impacting Lixian County arable land resources change are economic factor, demographic factor and progress in agricultural technology factor.

scholarly journals THE RELATIONSHIP BETWEEN CULTIVATED LAND CHANGE AND ECONOMIC DEVELOPMENT BASED ON GIS IN HENAN PROVINCE: AN EMPIRICAL STUDY

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 1013-1024
Author(s):  
C. Y. Lu ◽  
H. M. Zhang ◽  
F. Wen
Keyword(s):  
Economic Development ◽  
Path Dependence ◽  
Rapid Development ◽  
Henan Province ◽  
Cultivated Land ◽  
Land Change ◽  
Land Area ◽  
Land Occupation ◽  
Per Capita ◽  
The Relationship

Abstract. Cultivated land resources are the basic production factors that carry human survival and economic development. Exploring the relationship between cultivated land change and economic development has become a hot issue for scholars.in this paper,The methods of regression analysis, land use elastic coefficient method, location entropy are used to empirically describe the relationship between cultivated land change and economic development.The results show: Since the 20th century, the change of cultivated land area has experienced three distinct stages of change, showing a process of recovery, decline, and steady evolution in Henan Province. The per capita cultivated land area is characterized by an upward trend, and the per capita cultivated land area is increasing year by year. In general, the intensive use of cultivated land in Henan Province is still not high, but the momentum of a sharp decline in cultivated land is basically controlled. The change of cultivated land area and economic development showed a four-time curve fitting relationship, which indicates that the path dependence of economic development on cultivated land occupation still exists, and cultivated land supports the rapid development of economy.The research results of the relationship between cultivated land change and economic development by using location entropy show that the spatial layout of the urban area is less than 0, and the regularity is not strong.The location where the location entropy is between 0–1 is mainly located in the central part of Henan Province;The cities with location entropy greater than 1 are mainly located in the eastern part of Henan.

scholarly journals Multivariate visualization of the global COVID-19 pandemic: A comparison of 161 countries

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0252273
Author(s):  
Jane K. L. Teh ◽  
David A. Bradley ◽  
Jack Bee Chook ◽  
Kee Huong Lai ◽  
Woo Teck Ang ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Population Density ◽  
Principal Components ◽  
Principal Component ◽  
Component Analysis ◽  
Time Points ◽  
Global Spread ◽  
Multivariate Visualization ◽  
Per Capita ◽  
First 90 Days

Background The aim of the study was to visualize the global spread of the COVID-19 pandemic over the first 90 days, through the principal component analysis approach of dimensionality reduction. Methods This study used data from the Global COVID-19 Index provided by PEMANDU Associates. The sample, representing 161 countries, comprised the number of confirmed cases, deaths, stringency indices, population density and GNI per capita (USD). Correlation matrices were computed to reveal the association between the variables at three time points: day-30, day-60 and day-90. Three separate principal component analyses were computed for similar time points, and several standardized plots were produced. Results Confirmed cases and deaths due to COVID-19 showed positive but weak correlation with stringency and GNI per capita. Through principal component analysis, the first two principal components captured close to 70% of the variance of the data. The first component can be viewed as the severity of the COVID-19 surge in countries, whereas the second component largely corresponded to population density, followed by GNI per capita of countries. Multivariate visualization of the two dominating principal components provided a standardized comparison of the situation in the161 countries, performed on day-30, day-60 and day-90 since the first confirmed cases in countries worldwide. Conclusion Visualization of the global spread of COVID-19 showed the unequal severity of the pandemic across continents and over time. Distinct patterns in clusters of countries, which separated many European countries from those in Africa, suggested a contrast in terms of stringency measures and wealth of a country. The African continent appeared to fare better in terms of the COVID-19 pandemic and the burden of mortality in the first 90 days. A noticeable worsening trend was observed in several countries in the same relative time frame of the disease’s first 90 days, especially in the United States of America.

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